## `Security` in decorator `dependencies`

But for those additional responses you have to make sure you return a `Response` like `JSONResponse` directly, with your status code and content.

## Additional Response with `model`

You can pass to your *path operation decorators* a parameter `responses`.

It receives a `dict`: the keys are status codes for each response (like `200`), and the values are other `dict`s with the information for each of them.

      - tutorial/dependencies/index.md
      - tutorial/dependencies/classes-as-dependencies.md
      - tutorial/dependencies/sub-dependencies.md
      - tutorial/dependencies/dependencies-in-path-operation-decorators.md
      - tutorial/dependencies/global-dependencies.md
      - tutorial/dependencies/dependencies-with-yield.md
    - Security:
      - tutorial/security/index.md
      - tutorial/security/first-steps.md

## Recap

* Import `FastAPI`.
* Create an `app` instance.
* Write a **path operation decorator** using decorators like `@app.get("/")`.
* Define a **path operation function**; for example, `def root(): ...`.

compilation to JavaScript, it cannot rely on the types to define validation, serialization and documentation at the same time. Due to this and some design decisions, to get validation, serialization and automatic schema generation, it's needed to add decorators in many places. So, it becomes quite verbose.

It can't handle nested models very well. So, if the JSON body in the request is a JSON object that has inner fields that in turn are nested JSON objects, it cannot be properly documented and...

The important thing is that by using standard Python types, in a single place (instead of adding more classes, decorators, etc), **FastAPI** will do a lot of the work for you.

/// info

    * <a href="https://fastapi.tiangolo.com/tutorial/dependencies/dependencies-in-path-operation-decorators/" class="external-link" target="_blank">Tutorial - Dependencies - Dependencies in path operation decorators</a>.
    * <a href="https://fastapi.tiangolo.com/tutorial/dependencies/global-dependencies/" class="external-link" target="_blank">Tutorial - Dependencies - Global Dependencies</a>.

    * Add experimental supports conversion of models that may be larger than 2GB before buffer deduplication

### Bug Fixes and Other Changes

* `tf.py_function` and `tf.numpy_function` can now be used as function decorators for clearer code:
   ```
   @tf.py_function(Tout=tf.float32)
   def my_fun(x):
     print("This always executes eagerly.")
     return x+1
   ```

* `tf.lite`